Department of Entomology, Kansas State University, Manhattan, KS, 66506, USA.
Department of Statistics, Kansas State University, Manhattan, KS, 66506, USA.
Sci Rep. 2024 Jun 18;14(1):14053. doi: 10.1038/s41598-024-64841-8.
Sorghum aphid, Melanaphis sorghi (Theobald) have become a major economic pest in sorghum causing 70% yield loss without timely insecticide applications. The overarching goal is to develop a monitoring system for sorghum aphids using remote sensing technologies to detect changes in plant-aphid density interactions, thereby reducing scouting time. We studied the effect of aphid density on sorghum spectral responses near the feeding site and on distal leaves from infestation and quantified potential systemic effects to determine if aphid feeding can be detected. A leaf spectrometer at 400-1000 nm range was used to measure reflectance changes by varying levels of sorghum aphid density on lower leaves and those distant to the caged infestation. Our study results demonstrate that sorghum aphid infestation can be determined by changes in reflected light, especially between the green-red range (550-650 nm), and sorghum plants respond systemically. This study serves as an essential first step in developing more effective pest monitoring systems for sorghum aphids, as leaf reflection sensors can be used to identify aphid feeding regardless of infestation location on the plant. Future research should address whether such reflectance signatures can be detected autonomously using small unmanned aircraft systems or sUAS equipped with comparable sensor technologies.
高粱蚜虫，麦长管蚜（Theobald），已成为高粱的主要经济害虫，如果不及时使用杀虫剂，将导致 70%的产量损失。总体目标是利用遥感技术开发一种高粱蚜虫监测系统，以检测植物-蚜虫密度相互作用的变化，从而减少侦察时间。我们研究了蚜虫密度对受侵染近地和远地叶片高粱光谱响应的影响，并量化了潜在的系统效应，以确定是否可以检测到蚜虫取食。使用范围在 400-1000nm 的叶片分光光度计，通过改变下部叶片和远离受感染区域的叶片上的高粱蚜虫密度水平来测量反射率变化。我们的研究结果表明，通过反射光的变化，特别是在绿光-红光范围（550-650nm）之间，可以确定高粱蚜虫的侵染，并且高粱植物会产生系统性响应。本研究是开发更有效的高粱蚜虫害虫监测系统的重要第一步，因为叶片反射传感器可用于识别蚜虫取食，而无需考虑植株上的侵染位置。未来的研究应解决是否可以使用配备类似传感器技术的小型无人机系统或 sUAS 自主检测到这种反射特征。
